Floating point multiply-accumulate (FMAC) instructions are commonly used by microprocessors and microcontrollers. For example, mathematical matrix operations for graphics display often require several FMAC operations.
One important consideration in multiply-accumulate instructions is data dependency. Specifically, a multiply-accumulate instruction depends on operands whose values may change. In the case of parallel (pipelined) instruction processing, however, it cannot be assumed that each instruction is fully executed before execution of the subsequent instruction begins. Thus, an instruction may use incorrect operand values if the values have not settled from previous instructions. A potential error caused by data dependency is called a “hazard”. To address hazards, multiply-accumulate operations ordinarily delay until the values for each operand have settled from previous instructions. However, this solution leads to reduced processing speed. While other methods have been devised to address data dependency, these methods ordinarily require extra hardware such as large buffers or adders, adding to cost and space requirements.